Sr. Analyst - Quality

Job Description

Skill Set

• Databricks Testing

• Total Experience :

• 4.00 to 7.00 Years

• No of Openings :

• 1

• Job Post Date :

• 15/06/2026

• Job Expiry Date :

• 31/07/2026

• Domain :

• IT

• Location :

• PUNE [India]

• Job Reference No :

• 4085086

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• Job Summary

• Job Summary

• We are looking for a skilled ETL Test Engineer with Databricks experience to validate data pipelines, transformations, and data quality within a modern data platform. The ideal candidate should have strong expertise in ETL testing, SQL, big data technologies, and Databricks (Spark) .

• Key Responsibilities

• Design and execute test cases for ETL pipelines built on Databricks.

• Validate data transformations, data integrity, and data completeness across systems.

• Perform source to target mapping validation .

• Conduct data quality checks, data reconciliation, and regression testing .

• Write and execute complex SQL queries for validation.

• Validate batch and streaming data pipelines using Spark/Databricks.

• Collaborate with data engineers, analysts, and business teams .

• Automate test cases using Python / PySpark / testing frameworks .

• Monitor ETL jobs and troubleshoot data discrepancies and performance issues .

• Participate in CI/CD pipelines and test automation strategies .

• Required Skills

• Technical Skills

• Strong experience in ETL Testing / Data Warehouse Testing

• Hands on experience with Databricks (Spark, PySpark)

• Proficiency in SQL (advanced queries, joins, window functions)

• Knowledge of data lake, Delta Lake architecture

• Experience with big data technologies (Hadoop, Spark)

• Understanding of data validation frameworks

• Experience in test automation (Python/PySpark)

• Tools & Technologies

• Databricks

• Azure Data Factory / AWS Glue (optional but preferred)

• SQL tools (Snowflake, SQL Server, etc.)

• Testing tools (Selenium not mandatory, focus on backend testing)

• Git / CI CD tools

• Good to Have

• Experience with cloud platforms (Azure/AWS/GCP)

• Knowledge of data governance and data quality tools

• Experience with Agile/Scrum methodology

• Exposure to streaming data (Kafka, Spark Streaming)

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